jina-ai/embedding-inversion-demo
Embedding Inversion via Conditional Masked Diffusion: recover original text from embedding vectors using parallel denoising. Live demo + training pipeline + technical report.
This project helps security professionals and data privacy officers understand the reversibility of text embeddings. It takes an embedding vector, which is a numerical representation of text, and reconstructs the original words from it. This tool can be used by those concerned with data leakage or the potential for sensitive information to be recovered from supposedly anonymized text embeddings.
Use this if you need to assess the vulnerability of text embeddings to reconstruction attacks or demonstrate that seemingly irreversible text data can be recovered.
Not ideal if you are looking for a tool to generate text from scratch or to improve the quality of your text embeddings.
Stars
40
Forks
3
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 07, 2026
Commits (30d)
0
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